Handbook of Psychology, Volume 4: Experimental Psychology

98 Foundations of Visual Perception statesDorD
, and (b) on the scale of stimulus energy there is a fixed value below which obse ...

Psychophysical Methods 99 signal catch p(D|signal) p(“Yes”|D) p(D|signal) p(“Yes”|D) + = hit rate D D D D manipulable “Yes” “Yes ...

100 Foundations of Visual Perception Panel 5: The ROC Diagram. This panel differs from the corresponding one in Figure 4.1A beca ...

Psychophysical Methods 101 There are two ways to manipulate an observer’s guessing rate: (a) Manipulate the probability of a cat ...

102 Foundations of Visual Perception gain function in Figure 4.4). When it is used as a prescriptive framework, it is called an ...

Psychophysical Methods 103 differed in color (Figure 4.6A), shape (Figure 4.6B), or both (Figure 4.6C); they were called Differe ...

104Foundations of Visual Perception Variable Criterion The observers’task is to decide on every trial whether it was a signal tr ...

Psychophysical Methods 105 (We need not assume that observers actually use Bayes’s rule, only that they have a sense of the prio ...

106 Foundations of Visual Perception noise evidence density signal + noise evidence density phenomenal evidence phenomenal evide ...

Psychophysical Methods 107 Terman and Terman (1999) overcame the problem of hys- teresis by taking the mean of these two values ...

108 Foundations of Visual Perception (LTM). To determine the LTM, Barraza and Colombo (2001) showed the observers two gratings i ...

Psychophysical Methods109 converge onto the region around the threshold. In this they resemble the method of limits. But adaptiv ...

110 Foundations of Visual Perception Figure 4.17 Threshold search times as a function of the contrast of the letters against the ...

The “Structure” of the Visual Environment and Perception 111 not because the low-level features themselves are of interest for p ...

112 Foundations of Visual Perception In the remainder of this chapter we explore an instance of covariational analysis applied b ...

The “Structure” of the Visual Environment and Perception 113 “relative” to indicate that it was normalized such that the highest ...

114Foundations of Visual Perception withthereferenceelements;thatis,themostlikelyedgeele- mentscanbeconnectedthroughthecontourso ...

The“Structure” of the Visual Environment and Perception115 Thestimulusconsistsofasetofalignedlinesegments (arrangedinthisexample ...

116 Foundations of Visual Perception obtained in the one-parameter Bayesian local grouping func- tion (r=.89). In the conclusion ...

References 117 Feller, W. (1968). An introduction to probability theory and its applications.New York: Wiley. Field, D., Hayes, ...